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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Automatic computer-aided sacroiliac joint index analysis for bone scintigraphy.
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Automatic computer-aided sacroiliac joint index analysis for bone scintigraphy.

机译：自动计算机辅助sa关节指数分析，用于骨闪烁扫描。

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摘要

Bone scintigraphy helps to detect sacroiliitis before the radiographic changes. Nuclear medicine physicians interpret lesion on sacroiliac joint by the aid of sacroiliac joint-to-sacrum uptake ratios (sacroiliac joint index, SII). Usually, the SII is measured by manually drawing regions of interest (ROI) over the sacroiliac joints and sacrum, which is a tedious, time consuming, and highly operator dependent procedure. In this approach, we developed an automatic SII measurement program based on fuzzy sets histogram thresholding, anatomy-based image segmentation method and pelvis reference points located by morphological operations. To validate the program, the results of automatic SII measurement from 33 patients were compared with the results of manual SII measurement. For each patient, six SIIs representing the upper, middle, and low portions of the right and left SIIs were obtained. Totally, 198 SIIs were included for linear regression, bias, and precision analyses. The coefficient of determination (R(2)) between our approach and 2 medical experts' manual measurements are 0.923 and 0.917 respectively. The predictive performance (bias, precision) shows a good agreement result. From the result of this study, we expect that this automatic computer-aided approach may be applied to help nuclear medicine physicians in sacroiliitis interpretation.
机译：骨闪烁扫描有助于在影像学改变之前检测detect肌炎。核医学医师借助sa关节与s骨的摄取率（sa关节指数，SII）来解释on关节的病变。通常，通过手动绘制the关节和ac骨上的感兴趣区域（ROI）来测量SII，这是一个繁琐，耗时且高度依赖操作者的过程。在这种方法中，我们开发了一种基于模糊集直方图阈值化，基于解剖的图像分割方法以及通过形态学操作定位的骨盆参考点的自动SII测量程序。为了验证该程序，将33例患者的自动SII测量结果与手动SII测量结果进行了比较。对于每位患者，获得六个SII，分别代表左右SII的上部，中部和下部。总共包括198个SII，用于线性回归，偏差和精度分析。我们的方法与2位医学专家的手动测量之间的确定系数（R（2））分别为0.923和0.917。预测性能（偏差，精度）显示出良好的一致性结果。从这项研究的结果，我们期望这种自动的计算机辅助方法可以应用于帮助核医学医师进行sa关节炎的解释。

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